Many thousands of women die needlessly each year from breast cancer, a cancer from which there is theoretically a high probability of survival if detected sufficiently early. If the presence of cancerous tissue is missed in a sample, then, by the time the next test is undertaken, the cancer may have progressed and the chance of survival significantly reduced. The importance of detecting cancerous tissue in the samples can therefore not be over-emphasised.
A typical national breast screening programme uses mammography for the early detection of impalpable lesions. Once a lesion indicative of breast cancer is detected, then tissue samples are taken and examined by a trained histopathologist to establish a diagnosis and prognosis. More particularly, one of the principal prognostic factors for breast cancer is the extent of nuclear pleomorphism present in a sample. That is to say in normal tissue samples the nuclei of epithelial cells have a regular structure in terms of size and shape, whereas in cancerous tissue the nuclei can become larger and irregularly shaped, with a marked variation in shape and size.
In the existing manual procedure for grading nuclear pleomorphism a histopathologist places a slide under a microscope and examines a region of it (referred to as a tile) at a magnification of ×40 for variations in the size and shape of epithelial cell nuclei. His observations are then converted to a points score indicative of cancer grade typically in accordance with the following scheme:
Nuclear PleomorphismPoints ScoreSmall, uniform cells1Moderate nuclear size and variation2Marked nuclear variation3where a points score of 1 is the least serious and 3 is the most serious.
This is, however, a time consuming, labour intensive and expensive process. Qualification to perform such examination is not easy to obtain and requires frequent review. The examination itself requires the interpretation of colour images by eye, a highly subjective process characterised by considerable variations in both inter, and intra-observer analysis, i.e. variances in observation may occur for the same sample by different histopathologists, and by the same histopathologist at different times. For example, studies have shown that two different histopathologists examining the same ten samples may give different opinions on three of them, an error of 30%. This problem is exacerbated by the complexity of some samples, especially in marginal cases where there may not be a definitive conclusion. If sufficient trained staff are not available this impacts upon pressures to complete the analysis, potentially leading to erroneous assessments and delays in diagnosis.
These problems mean that there are practical limitations on the extent and effectiveness of screening for breast cancer with the consequence that some women are not being correctly identified as having the disease and, on some occasions, this failure may result in premature death. Conversely, others are being incorrectly diagnosed with breast cancer and therefore undergoing potentially traumatic treatment unnecessarily.
It is thus an aim of the invention to provide an automated method of image analysis which can be embodied in a robust, objective and cost-effective tool to assist in the diagnosis and prognosis of breast cancer, although as previously indicated the invention may also find application in other fields.
In one aspect the invention accordingly resides in a method for the automated analysis of a digital image comprising an array of pixels, including the steps of: identifying the locations of objects within the image which have specified intensity and size characteristics; deriving respective boundaries for respective such objects; assessing the significance of objects based on statistics concerning at least the shapes of their respective derived boundaries; and calculating a measure of the variability of at least the areas enclosed by said derived boundaries subject to the results of said assessment of significance.
As will be understood from the ensuing detailed description of preferred embodiments, such a method is of use in grading nuclear pleomorphism from images of histopathological slides.
The invention also resides in apparatus for the automated analysis of a digital image comprising means to perform the foregoing method and in a computer program product comprising a computer readable medium having thereon computer program code means adapted to cause a computer to execute the foregoing method and in a computer program comprising instructions so to do.
These and other aspects of the invention will now be more particularly described, by way of example, with reference to the accompanying drawings and in the context of an automated system for grading cancer on the basis of the assessment of epithelial cell nuclear pleomorphism in digital images of histopathological slides of potential carcinomas of the breast.